Neuromonitoring is a subfield of clinical patient monitoring focused on measuring various aspects of brain function and on changes therein caused by neurological diseases, accidents, and drugs commonly used to induce and maintain anesthesia in an operation room or sedation in patients under critical or intensive care.
Electroencephalography (EEG) is a well-established method for assessing brain activity. When measurement electrodes are attached on the skin of the skull surface, the weak biopotential signals generated in brain cortex may be recorded and analyzed. The EEG has been in wide use for decades in basic research of the neural systems of the brain as well as in the clinical diagnosis of various central nervous system diseases and disorders.
The EEG signal represents the sum of excitatory and inhibitory potentials of large numbers of cortical pyramidal neurons, which are organized in columns. Each EEG electrode senses the average activity of several thousands of cortical pyramidal neurons.
The EEG signal is often divided into four different frequency bands: Delta (0.5-3.5 Hz), Theta (3.5-7.0 Hz), Alpha (7.0-13.0 Hz), and Beta (13.0-32.0 Hz). In an adult, Alpha waves are found during periods of wakefulness, and they may disappear entirely during sleep. Beta waves are recorded during periods of intense activation of the central nervous system. The lower frequency Theta and Delta waves reflect drowsiness and periods of deep sleep.
While spontaneous variation in a wake-sleep cycle causes physiological and rapidly reversible changes in the EEG, different derangements of internal system homeostasis disturb the environment in which the brain operates, and therefore the function of the brain and the resulting EEG are disturbed. The EEG signal is a very sensitive measure of the neuronal derangements, which may reflect in the EEG signal either as changes in membrane potentials or as changes in synaptic transmission. A change in synaptic transmission occurs whenever there is an imbalance between consumption and supply of energy in the brain. This means that the EEG signal serves as an early warning of a developing injury in the brain.
Generally, if a patient is unconscious (without sedation), the reason in 30 to 40 percent of the cases is intracranial, whereas in 60 to 70 percent of the cases unconsciousness is due to hypoxic-ischaemic, metabolic, or toxic reasons. This kind of general unconsciousness is currently monitored with the help of the Glasgow Coma Scale (GCS). It defines the patient (un)consciousness by using three parameters: the best eye opening response, the best motoric response, and best response to speech. The final score represents the sum of the scores of the three categories. Table 1 below illustrates the Glasgow Coma Scale. Although the Glasgow Coma Scale is subjective and inter-rater variability may exist, it is the most widely used scoring system to assess patients with traumatic brain injury, for example.
TABLE 1The Glasgow Coma ScaleCriterionPointsEye Opening ResponseSpontaneous4Opens to verbal command3Opens to pain2None1Verbal responseOriented5Confused4Inappropriate words3Incomprehensible sounds2None1Motor responseObeys commands6Localises pain5Withdraws from pain4Abnormal flexion3Extends to pain2None1Total3-15
Diagnostically, the EEG is only rarely specific, since many systemic disorders of the brain produce similar EEG manifestations. However, an EEG signal may be of critical value, as it may differentiate between broad categories of psychogenic, epileptic, metabolic-toxic, encephalitic, and focal conditions, for example.
In a healthy sleeping subject, the EEG is reactive to various stimuli according to the sleep stages. For a comatose patient, a test of the reactivity of the EEG signal to external stimulation is an important assessment tool for a clinician, since it provides significant information regarding the state and outcome of the patient. EEG reactivity may reveal potentially treatable conditions and also provide information of the level of drug-induced sedation. While some conclusions about the probability of a recovery can be drawn from the raw EEG signal as such, it has been shown that reactivity of the EEG signal to stimulation, i.e. a detectable change in the EEG signal after a stimulus as compared to the pre-stimulus situation, is a more specific indicator of a favourable outcome, cf. G. B. Young, et al: An Electroencephalographic Classification for Coma, Can. J. Neurol. Sci. 1997; 24: 320-325. Therefore, testing the EEG reactivity is an essential part of the EEG examination of a comatose patient. Moreover, the test of EEG reactivity provides information regarding the state of a patient for whom the GCS or another observational scoring system is not applicable. This is the case, for example, when neuromuscular blocking agents have been administered to the patient, which makes the patient unable to respond and thus the observational scoring systems inapplicable.
At present, the EEG reactivity is assessed by an EEG specialist trained to interpret EEG waveforms. In practice, ICU (Intense Care Unit) doctors or nurses, who are skilled in making GCS-type assessments, are usually not capable of interpreting the EEG waveforms, and therefore a consulting EEG specialist has to be called in for the test of EEG reactivity. Various types of stimuli, such as auditory (shouting the patient's name, blowing a horn) and somatosensory (pinching the skin, squeezing nail beds, shaking) stimuli, may be applied in the test. The EEG specialist annotates the time instant of the stimulation and compares the recorded EEG signal before and after the annotated time instant. Often the EEG signal shows reactivity only to some of the given stimuli; in this case reactivity is considered to be present.
The test of the EEG reactivity is thus currently based on the visual assessment of the EEG waveform prior to and after the stimulation, since developing an automated testing procedure is complicated. This is mainly due to the high inter-patient variability, which may cause great variations between different patients both in the initial EEG signal waveforms and in the reactions to stimuli. The initial EEG signal waveforms, for example, may vary greatly depending on the state of the patient. The reactions that may be seen in the EEG signal after the stimulation comprise different types of responses, such as slow wave responses, voltage reduction and filtering of remnants of the basic rhythm, and flattening of voltage without or with blocking of slow waves, cf. Ernst Niedermayer, Fernando Lopes da Silva: Electroencephalography: basic principles, clinical applications, and related fields, p. 462, fourth edition, 1998, ISBN 0-683-30284-1. The visual assessment of the EEG is performed by a specialist, since he/she must understand the features of the EEG and take into account various patient-specific factors, such as the age, the level of drowsiness, and the metabolic state of the patient, as well as the possible disorders and their effect on the basic EEG signal.
Due to the above-described high variability between different patients, no automatic quantification tools exist for assessing the EEG reactivity, but a specialist is needed for the interpretation of the EEG waveforms. Consequently, the assessments are subjective and dependent on the level of expertise of the specialist.
The present invention seeks to alleviate or eliminate the above-mentioned drawback and to devise an automated mechanism for evaluating EEG reactivity.